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Urinary Volatile Organic Compounds for the Detection of Prostate Cancer

The aim of this work was to investigate volatile organic compounds (VOCs) emanating from urine samples to determine whether they can be used to classify samples into those from prostate cancer and non-cancer groups. Participants were men referred for a trans-rectal ultrasound-guided prostate biopsy...

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Detalles Bibliográficos
Autores principales: Khalid, Tanzeela, Aggio, Raphael, White, Paul, De Lacy Costello, Ben, Persad, Raj, Al-Kateb, Huda, Jones, Peter, Probert, Chris S., Ratcliffe, Norman
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4657998/
https://www.ncbi.nlm.nih.gov/pubmed/26599280
http://dx.doi.org/10.1371/journal.pone.0143283
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author Khalid, Tanzeela
Aggio, Raphael
White, Paul
De Lacy Costello, Ben
Persad, Raj
Al-Kateb, Huda
Jones, Peter
Probert, Chris S.
Ratcliffe, Norman
author_facet Khalid, Tanzeela
Aggio, Raphael
White, Paul
De Lacy Costello, Ben
Persad, Raj
Al-Kateb, Huda
Jones, Peter
Probert, Chris S.
Ratcliffe, Norman
author_sort Khalid, Tanzeela
collection PubMed
description The aim of this work was to investigate volatile organic compounds (VOCs) emanating from urine samples to determine whether they can be used to classify samples into those from prostate cancer and non-cancer groups. Participants were men referred for a trans-rectal ultrasound-guided prostate biopsy because of an elevated prostate specific antigen (PSA) level or abnormal findings on digital rectal examination. Urine samples were collected from patients with prostate cancer (n = 59) and cancer-free controls (n = 43), on the day of their biopsy, prior to their procedure. VOCs from the headspace of basified urine samples were extracted using solid-phase micro-extraction and analysed by gas chromatography/mass spectrometry. Classifiers were developed using Random Forest (RF) and Linear Discriminant Analysis (LDA) classification techniques. PSA alone had an accuracy of 62–64% in these samples. A model based on 4 VOCs, 2,6-dimethyl-7-octen-2-ol, pentanal, 3-octanone, and 2-octanone, was marginally more accurate 63–65%. When combined, PSA level and these four VOCs had mean accuracies of 74% and 65%, using RF and LDA, respectively. With repeated double cross-validation, the mean accuracies fell to 71% and 65%, using RF and LDA, respectively. Results from VOC profiling of urine headspace are encouraging and suggest that there are other metabolomic avenues worth exploring which could help improve the stratification of men at risk of prostate cancer. This study also adds to our knowledge on the profile of compounds found in basified urine, from controls and cancer patients, which is useful information for future studies comparing the urine from patients with other disease states.
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spelling pubmed-46579982015-12-02 Urinary Volatile Organic Compounds for the Detection of Prostate Cancer Khalid, Tanzeela Aggio, Raphael White, Paul De Lacy Costello, Ben Persad, Raj Al-Kateb, Huda Jones, Peter Probert, Chris S. Ratcliffe, Norman PLoS One Research Article The aim of this work was to investigate volatile organic compounds (VOCs) emanating from urine samples to determine whether they can be used to classify samples into those from prostate cancer and non-cancer groups. Participants were men referred for a trans-rectal ultrasound-guided prostate biopsy because of an elevated prostate specific antigen (PSA) level or abnormal findings on digital rectal examination. Urine samples were collected from patients with prostate cancer (n = 59) and cancer-free controls (n = 43), on the day of their biopsy, prior to their procedure. VOCs from the headspace of basified urine samples were extracted using solid-phase micro-extraction and analysed by gas chromatography/mass spectrometry. Classifiers were developed using Random Forest (RF) and Linear Discriminant Analysis (LDA) classification techniques. PSA alone had an accuracy of 62–64% in these samples. A model based on 4 VOCs, 2,6-dimethyl-7-octen-2-ol, pentanal, 3-octanone, and 2-octanone, was marginally more accurate 63–65%. When combined, PSA level and these four VOCs had mean accuracies of 74% and 65%, using RF and LDA, respectively. With repeated double cross-validation, the mean accuracies fell to 71% and 65%, using RF and LDA, respectively. Results from VOC profiling of urine headspace are encouraging and suggest that there are other metabolomic avenues worth exploring which could help improve the stratification of men at risk of prostate cancer. This study also adds to our knowledge on the profile of compounds found in basified urine, from controls and cancer patients, which is useful information for future studies comparing the urine from patients with other disease states. Public Library of Science 2015-11-24 /pmc/articles/PMC4657998/ /pubmed/26599280 http://dx.doi.org/10.1371/journal.pone.0143283 Text en © 2015 Khalid et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Khalid, Tanzeela
Aggio, Raphael
White, Paul
De Lacy Costello, Ben
Persad, Raj
Al-Kateb, Huda
Jones, Peter
Probert, Chris S.
Ratcliffe, Norman
Urinary Volatile Organic Compounds for the Detection of Prostate Cancer
title Urinary Volatile Organic Compounds for the Detection of Prostate Cancer
title_full Urinary Volatile Organic Compounds for the Detection of Prostate Cancer
title_fullStr Urinary Volatile Organic Compounds for the Detection of Prostate Cancer
title_full_unstemmed Urinary Volatile Organic Compounds for the Detection of Prostate Cancer
title_short Urinary Volatile Organic Compounds for the Detection of Prostate Cancer
title_sort urinary volatile organic compounds for the detection of prostate cancer
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4657998/
https://www.ncbi.nlm.nih.gov/pubmed/26599280
http://dx.doi.org/10.1371/journal.pone.0143283
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